README.md
In unitquantreg: Parametric Quantile Regression Models for Bounded Data

Welcome to `unitquantreg` R package

The goal of unitquantreg is to provide tools for estimation and inference on parametric quantile regression models for bounded data.

We developed routines with similar interface as stats::glm function, which contains estimation, inference, residual analysis, prediction, and model comparison.

For more computation efficient the [dpqr]’s, likelihood, score and hessian functions are vectorized and written in C++.

You can install the stable version from CRAN with:

install.packages("unitquantreg")

Or you can install the development version from GitHub with:

if(!require(remotes)) install.packages('remotes')
remotes::install_github("AndrMenezes/unitquantreg", build_vignettes = TRUE)

You can then load the package

library(unitquantreg)

and look at user manuals typing:

vignette("unitquantreg")
vignette("structure_functionality")

citation("unitquantreg")
#> 
#> To cite unitquantreg in publications use:
#> 
#>   Menezes A, Mazucheli J (2021). _unitquantreg: Parametric quantile
#>   regression models for bounded data_. R package version 0.0.3,
#>   <https://andrmenezes.github.io/unitquantreg/>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {unitquantreg: {P}arametric quantile regression models for bounded data},
#>     author = {Andr{'}e F. B. Menezes and Josmar Mazucheli},
#>     note = {R package version 0.0.3},
#>     url = {https://andrmenezes.github.io/unitquantreg/},
#>     year = {2021},
#>   }

The unitquantreg package is released under the Apache License, Version 2.0. Please, see file LICENSE.md.